An Improvement Object Detection Method Findcontour with Fuzzy Logic for Detect Balinese Script Object

Ida Bagus Putra Manuaba, K. Indah, Muhammad Fahmi, Irma, Nuraeni Salsabila
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引用次数: 2

Abstract

The function of OpenCV can be used as a method for detecting Balinese script objects . Experiments to detect Balinese script using this function are able to detect all objects that are on palm leaf media. Objects that have been detected are literal objects and non-literal objects. This study aims to improve the detection method with the findcontour function by adding a fuzzy algorithm, to separate Balinese script objects from non-Balinese characters. The data in this study were in the form of Balinese script written on palm leaves. The Balinese manuscripts used as data in the research are new manuscripts that were deliberately written for research purposes. Fuzzy logic in this study is used to determine objects that have been detected, including script objects or not. The results are visible from the detected objects, fuzzy logic is able to eliminate 400 - 5000 objects that are not needed. Meanwhile, in terms of time, the filtering process with fuzzy logic has an impact on the ROI process being faster with an average time of less than 1 second.
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一种改进的基于模糊逻辑的目标检测方法Findcontour用于检测巴厘文字对象
OpenCV的功能可以作为检测巴厘语脚本对象的方法。使用此功能检测巴厘文字的实验能够检测到棕榈叶媒体上的所有物体。检测到的对象有文字对象和非文字对象。本研究旨在改进findcontour函数的检测方法,加入模糊算法,将巴厘文字对象与非巴厘文字区分开来。本研究的资料是以写在棕榈叶上的巴厘文字的形式。作为研究数据的巴厘手稿是特意为研究目的而写的新手稿。在本研究中,模糊逻辑用于确定已检测的对象,包括脚本对象与否。结果从检测到的对象中可见,模糊逻辑能够剔除400 - 5000个不需要的对象。同时,在时间方面,模糊逻辑滤波过程对ROI过程的影响更快,平均时间小于1秒。
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